The healthcare industry faces arguably the highest stakes when it comes to data governance. For starters, healthcare organizations constantly encounter vast (and ever-increasing) amounts of highly regulated personal data. The impact of healthcare data usage on people’s lives lies at the heart of why data governance in healthcare is so crucial.
In healthcare, managing the accuracy, quality and integrity of data is the focus of data governance. When healthcare organizations excel at this, it can lead to better clinical decision-making, improved patient outcomes and prevention of medical errors. Despite this, many healthcare organizations face challenges. Healthcare organizations need a strong data governance framework to help ensure compliance with regulations like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the US and the General Data Protection Regulation (GDPR) in the EU. How can a healthcare provider improve its data governance strategy, especially considering the ripple effect of small changes? Data lineage can help.
With data lineage, your team establishes a strong data governance strategy, enabling them to gain full control of your healthcare data pipeline. Understanding data governance in healthcare The need for a strong data governance framework is undeniable in any highly-regulated industry, but the healthcare industry is unique because it collects and processes massive amounts of personal data to make informed decisions about patient care. One broken or incomplete piece of data can trigger not only noncompliance and audit issues but also harm real people. For example: Healthcare providers regularly rely on medical records to diagnose and establish treatment plans for patients. Inaccuracies in these medical records leading to misdiagnoses, medication errors or delayed care can have serious consequences. Inaccuracies might also lead to more delays or complications with insurance coverage.
Healthcare organizations must adhere to data privacy regulations like HIPAA and GDPR. Noncompliance with these laws is costly and can damage your reputation, besides posing a danger to patients and practitioners when data breaches occur. Conversely, confidence in the accuracy and consistency of your data can minimize the risk of adverse health outcomes, rather than merely reacting to or causing them. Also, using predictive analytics can help identify trends, patterns and potential future health risks in your patients. It’s worth noting that most electronic health records (EHR) systems offer predictive analytics capabilities. The accuracy of these analytics is limited by the accuracy of the data used. Thus, having a comprehensive understanding of the data environment and a clear chain of custody becomes imperative. Detecting leaks and pressure points depends on implementing a strong data governance strategy, with data lineage as a critical component.
Challenges in data governance for healthcare and how data lineage can help Data governance can help healthcare organizations maximize the accuracy and security of their data assets. At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. 1. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data. However, healthcare facilities continue to face data quality issues despite the best efforts of business leaders, primarily due to the sheer number of people inputting data and the high-pressure situations in which data entry often occurs. A study conducted by the Journal of the American Medical Association (JAMA) revealed that errors were found in the records of one-fifth of patients with access to ambulatory care notes. Among those patients, 21% identified the errors as critical, with common issues including diagnostic errors, medication data errors and incomplete or inaccurate EHR data conversions. These errors are crucial and can occur daily. To prevent these errors, it’s critical for data flows to be mapped out and for issues with data quality to be flagged by using root-cause analysis, thereby reducing the impact on patients.
2. Data silos In the healthcare industry, where an estimated 30% of the world’s total data is generated, patient data often remains unstructured and scattered across disparate systems. The consequence? An incomplete picture of patient health and multiple sources of truth prevents you from achieving the benefits of data visibility such as informed patient care. Issues with compliance and audit conduct also arise due to these scattered data sources. The solution lies in the ability to visualize patient data from different sources in one place. That’s exactly what enterprise-wide data lineage does. Data lineage extends throughout your data environment to create a comprehensive map of all your data flows and dependencies, eliminating data silos effectively. However, not all data lineage solutions can visualize data from different silos. Some platforms only allow you to see data stored within their specific catalog. Opting for a catalog-agnostic solution helps you address this issue.
3. Security concerns and chain of custody Healthcare organizations are in a unique position because both depend on cross-departmental information sharing to facilitate patient care and are bound by strict regulations to help ensure secure data transmission. As part of both HIPAA and GDPR compliance, healthcare organizations need to provide auditors with details regarding the chain of custody of patient records. This includes information on who accessed the records and the time and location of access. Establishing a chain of custody for data stored in an EHR system accessible across several devices within a medical facility can be laborious and time-intensive, especially when dealing with so many records that exist in a paper format or have been manually entered or scanned. Data lineage significantly reduces the amount of effort needed to establish a chain of custody within healthcare information systems. By mapping data flows, you can trace the journey of your data backward to see where and when it was changed in your systems. Combined with your governance efforts that establish the meaning, quality and stewardship of the data stores in this chain of custody, you can deliver the crucial data pipeline information required by your auditors. Better patient care and predictive analytics With high-quality data, you can provide well-informed, cross-collaborative and personalized patient care. You also place deeper trust in the predictive analytics within your EHR system to predict patient conditions, disease progression, hospital overstays, readmissions, and more. All this relies on reliable data and requires data lineage for governance. Enhanced regulatory compliance If you’re struggling with data silos, data quality or proving chain of custody, you might also be finding it difficult to establish and prove compliance with healthcare-related regulations like HIPAA and GDPR. Data lineage can help you establish your chain of information flow and dependencies to auditors clearly and quickly, which is key to compliance. Increased data security and privacy In the healthcare industry, data privacy is integral. When data lineage creates a map of your data environment, it does so without sharing or processing any private information. Instead, it uses active metadata. That means that you can create a strong data governance framework without sacrificing patient privacy. Improved operational efficiency and cost savings Mapping out data flows manually is a time and resource-intensive process, especially in the highly-complex healthcare industry. Among the top advantages of automated data lineage for data governance are its operational efficiency and cost-effectiveness. You can save money and time on labor costs and focus your efforts on what matters most to your organization. We’re 90% faster “Our ETL teams can identify the impacts of planned ETL process changes 90% faster than before.” Robert D, BI Team Leader at GEMU 90% increase in analyzing source system changes “Effort for analyzing the impact of a source system change has decreased by at least 90%, from hours to minutes (or seconds).” Michael L., BI Manager at Schumacher Clinical Data governance and compliance In the healthcare industry, ensuring compliance with regulations like HIPAA and GDPR is another important piece of data governance, crucial for both protecting patient privacy and facilitating secure information-sharing critical for the highest level of patient care. Some healthcare organizations today still struggle to maintain compliance with HIPAA and GDPR. Meanwhile, the world’s regulatory landscape is becoming increasingly complex. In fact, Gartner® predicts that by the end of 2024, 75% of the world will have its data protected under modern privacy regulations. Given that the healthcare industry is generating new regulated patient data by the second, now is the time to kickstart an effective data governance strategy. It’s worth noting that these regulations don’t just apply to patient care-focused organizations. Nearly every area of healthcare processed large quantities of protected data, including: Biotechnology companies Health insurance providers Medical device manufacturers Pharmaceutical companies With data lineage, you get a detailed map of your data flows that help ensure…
